Summer Reading: Complexity, Continuity, Math, and Leadership

This was one of the deepest and most interesting books I read all year. Wimsatt is a philosopher, but early in his career he did tours through physics and biology. This helps to ground his material in real scientific contexts, especially in the history of genetic theory.

Some favorite quotes:

“Why is it that academics who claim to seek the truth want to pretend that they have always had it?”

“The history of scientific progress and the evolution of our conceptual categories is littered with one generation’s projects and category mistakes that have become the next generation’s impossibilities and conceptual truths.”

“Cognitively speaking, we metabolize mistakes!”

Heuristics

Wimsatt is a big fan of Herbert Simon’s model of man as “satisficer,” and notes how suited heuristics are for the temporal and cognitive limitations we’re faced with. He even draws a parallel to evolutionary biology, claiming that biological adaptations also meet the definition of a heuristic.

The chapter “False Models as Means to Truer Theories” is a tour de force through the nature of models and why it’s still useful to construct them even when they may not be comprehensive or 100% true in all cases. He provides several examples from the history of genetics for how a theory that was not quite right was able to spur insights into a deeper understanding of how genes worked.

Wimsatt is very detailed and enumerates qualities and definitions for many abstract ideas that are above and beyond what I’ve typically seen. For instance, he gives a definition of a heuristic based on three qualities:

“The correct application of a heuristic procedure does not guarantee a solution and, if it produces a solution, does not guarantee that the solution is correct.”

Heuristics are “a cost-effective way, and often the only physically possible way, of producing a solution.” “The application of a heuristic to a problem yields a transformation of the problem to a nonequivalent but intuitively related problem, [meaning] answers to the transformed problem may not be answers to the original problem.”

“The failures and errors produced when a heuristic is used are not random but systematic. …any heuristic, once we understand how it works, can be made to fail. … This property of systemic production of wrongs answers will be called the bias of the heuristic.”

Mental Models

Wimsatt introduces several valuable mental models:

Robustness analysis: Something (an entity, concept, pattern or theory) is robust to the degree that it is accessible via multiple independent means. With this in mind, we might order the laws of nature by fundamentality: “the more fundamental laws will be those that are independently derivable in a larger number of ways.”

Wimsatt goes on to describe what’s elsewhere called thinking from First Principles: a reasoning process involving just a few short jumps from fundamental laws and principles will do much better than a long, serial chain of reasoning. “We feel more confident of objects, properties, relationships, and so forth that we can detect, derive, measure, or observe in a variety of independent ways because the chance that we could be simultaneously wrong in each of these ways declines with the number of independent checks we have.”

Generative entrenchment: Wimsatt’s idea of generative entrenchment is deeply tied to evolutionary processes. As organisms or systems evolve, certain changes become more critical than others because they help generate other adaptations. An example would be the emergence of RNA and DNA, which have become generatively entrenched in so much of biological life due to their unlocking of many more adaptations. Other examples would be the joint-stock company or Bitcoin (kicked off Blockchain + ICO ‘revolutions’).

“A deeply generatively entrenched feature of a structure is one that has many other things depending on it because it has played a role in generating them. It is an inevitable characteristic of evolved systems of all kinds – biological, cognitive, or cultural – that different elements of the system show differential entrenchment.” Generatively entrenched features engender and result in positive feedback loops: as more things build on a platform that platform becomes more entrenched, making it more stable and unlikely to change, therefore more things get built on it, etc.

Perspectives and causal thickets: These are close analogs to Charlie Munger’s latticework of mental models. When a phenomenon is complex enough that it requires multiple explanations that cross boundaries (both physical or theoretical), Wimsatt labels the multi-disciplinary view for that phenomenon a “perspective” (rather than just a single explanation from a theory of physics or biology). Wimsatt considers that there are aspects of reality that still don’t yield themselves to explanation by perspectives, these areas of reality he calls “causal thickets.” I love this term as it calls to mind a shrub, where every branch is a theory or explanation that might be valid but is only a minor, intermingled part of the picture. Examples of causal thickets are abundant in the realms of psychology and sociology.

The Ontology of Complex Systems

I’ve always been fascinated by how nature seems to operate at levels. Why is it that we seem able to stack fields and theories on top of one another, such as Physics > Chemistry > Biology > Sociology? Wimsatt explores why these occur in nature and complex systems. One answer has to do with the size of things in nature: because the size of something means it’s likely to interact with other things of equivalent size, our theories become robust at those levels (e.g. we have more means of proving and providing examples of a given theory at that level).

Wimsatt spends a good deal of the book outlining a subtle position on reductionism. It’s easy for us to read books about complexity and emergence then develop a distasteful attitude for simple reductive explanations. But Wimsatt shows that reality isn’t even simple enough to contain solely reductive OR emergent phenomena. Reductive explanations still have their place in describing nature accurately.

Wimsatt believes our world is like graphs (a) or (c) above. Below, he draws the progression from simple reductionist theories, through emergence, and then causal thickets.

A quick read on leadership principles. Aside from the Iraqi war anecdotes, which were interesting in their own right, most of the ideas are things you’ve probably heard before. But that doesn’t mean it’s not worth it to be reminded of them.

I went on a big math kick these past few months. Frenkel’s book is a good introduction to modern mathematics that isn’t too tough for a layperson. The book is worth it for his explanation of symmetry alone, although there were a few parts where he gets carried away.

I’ve not read anything near all of this volume, but made a dent in the first few chapters and skipped around as various topics interested me. More of an encyclopedia than something you read cover-to-cover, it’s great to have around as you’re exploring math topics.

Thom was an influential mathematician from the last century who invented catastrophe theory and did lots of work in topology. I have a large personal fascination with the dichotomy between the continuous and the discrete. When and where is it helpful to treat a system as analog or digital, continuous or discrete? Is reality fundamentally one or the other? While no-one can really know, I have a soft-spot for people in the predominantly continuous/analog camp, such as Thom and CS Peirce.

Peirce is one of my favorite philosophers and this book is an exploration and expansion of his theories of continuity. Most discussions of continuity by mathematicians stop at Cantor’s real number line (or the related Zeno’s paradox), but as Zalamea shows, Peirce’s concept of continuity is a much more metaphysical idea that goes deeper. I loved the first half of the book but struggled through the latter half, when he dives into Peirce’s existential graphs. I’m still working up to see the real beauty and utility people ascribe to these tools developed by Peirce.

More Peirce-inspired, continuity-related stuff, from a philosophy/semiotic point of view. Probably not worth it if you’re not into this sort of thing. I do find it interesting that Maddelanas’ models for synthetic judgment bear a lot of similarity to Wimsatt’s perspectives and causal thickets.

I’ve not read this cover-to-cover yet, but only because I’ve listened to so many of his podcast episodes which cover a lot of the same territory. I’ve come to love Peterson’s work. I grew up with a largely Catholic upbringing, surrounded by stories from the Bible that I struggled to take too literally. Peterson offers a synthetic perspective on some of our oldest stories that bring together evolution, psychology, and historical fact. Even if we find it hard to believe in the literal tale of Adam and Eve or the fratricide between their sons, Cain and Abel, Peterson shows how these stories are generic examples of humanity’s struggle with its own limitations. These stories play themselves out over and over again across time and different cultures, so even if they may not be true as historical fact they are very, robustly true as descriptions of human nature (see Wimsatt’s definition of robustness). I can’t help but point out the parallels between his framing of chaos and uncertainty and the same Peircean continuity described earlier.

I bought this book after seeing it recommended on Chet Richards’ blog. It’s another great work of synthesis that brings together theories from John Boyd, Gregory Bateson and other systems-thinkers (but not many business gurus!). I really liked their use of landscapes to visualize strategic positioning:

A quick-read business book about urgency. I’ve thought about this a lot as it relates to distinctions between real vs. manufactured urgency, and how to increase one over the other. This wasn’t mind-blowing but still had some good reminders.